Adapted fan-beam volume reconstruction for stationary digital breast tomosynthesis

Abstract

Digital breast tomosynthesis (DBT) provides 3D images which remove tissue overlapping and enables better cancer detection. Stationary DBT (s-DBT) uses a fixed X-ray source array to eliminate image blur associated with the x-ray tube motion and provides better image quality as well as faster scanning speed. For limited angle tomography, it is known that iterative reconstructions generally produces better images with fewer artifacts. However classical iterative tomosynthesis reconstruction methods are considerably slower than the filtered back-projection (FBP) reconstruction. The linear x-ray source array used in s-DBT enables a computationally more efficient volume reconstruction using adapted fan beam slice sampling, which transforms the 3-D cone beam reconstruction to a series of 2-D fan beam slice reconstructions. In this paper, we report the first results of the adapted fan-beam volume reconstruction (AFVR) for the s-DBT system currently undergoing clinical trial at UNC, using a simultaneous algebraic reconstruction technique (SART). An analytic breast phantom is used to quantitatively analyze the performance of the AFVR. Image quality of a CIRS biopsy phantom reconstructed using the AFVR method are compared to that using FBP algorithm with a commercial package. Our results show a significant reduction in memory usage and an order of magnitude speed increase in reconstructing speed using AFVR compared to that of classical 3-D cone beam reconstruction. We also observed that images reconstructed by AFVR with SART had a better sharpness and contrast compared to that using FBP. Preliminary results on patient images demonstrates the improved detectability of the s-DBT system over the mammography. By utilizing parallel computing with graphics processing unit (GPU), it is expected that the AFVR method will enable iterative reconstruction technique to be practical for clinical applications.